PDF(Pubmed)
Abstract：
UNASSIGNED: Accumulating evidence reveals mitochondrial dysfunction exacerbates intestinal barrier dysfunction and inflammation. Despite the growing knowledge of mitochondrial dysfunction and ulcerative colitis (UC), the mechanism of mitochondrial dysfunction in UC remains to be fully explored.
UNASSIGNED: We integrated 1137 UC colon mucosal samples from 12 multicenter cohorts worldwide to create a normalized compendium. Differentially expressed mitochondria-related genes (DE-MiRGs) in individuals with UC were identified using the \"Limma\" R package. Unsupervised consensus clustering was utilized to determine the intrinsic subtypes of UC driven by DE-MiRGs. Weighted gene co-expression network analysis was employed to investigate module genes related to UC. Four machine learning algorithms were utilized for screening DE-MiRGs in UC and construct MiRGs diagnostic models. The models were developed utilizing the over-sampled training cohort, followed by validation in both the internal test cohort and the external validation cohort. Immune cell infiltration was assessed using the Xcell and CIBERSORT algorithms, while potential biological mechanisms were explored through GSVA and GSEA algorithms. Hub genes were selected using the PPI network.
UNASSIGNED: The study identified 108 DE-MiRGs in the colonic mucosa of patients with UC compared to healthy controls, showing significant enrichment in pathways associated with mitochondrial metabolism and inflammation. The MiRGs diagnostic models for UC were constructed based on 17 signature genes identified through various machine learning algorithms, demonstrated excellent predictive capabilities. Utilizing the identified DE-MiRGs from the normalized compendium, 941 patients with UC were stratified into three subtypes characterized by distinct cellular and molecular profiles. Specifically, the metabolic subtype demonstrated enrichment in epithelial cells, the immune-inflamed subtype displayed high enrichment in antigen-presenting cells and pathways related to pro-inflammatory activation, and the transitional subtype exhibited moderate activation across all signaling pathways. Importantly, the immune-inflamed subtype exhibited a stronger correlation with superior response to four biologics: infliximab, ustekinumab, vedolizumab, and golimumab compared to the metabolic subtype.
UNASSIGNED: This analysis unveils the interplay between mitochondrial dysfunction and the immune microenvironment in UC, thereby offering novel perspectives on the potential pathogenesis of UC and precision treatment of UC patients, and identifying new therapeutic targets.
UNASSIGNED: We integrated 1137 UC colon mucosal samples from 12 multicenter cohorts worldwide to create a normalized compendium. Differentially expressed mitochondria-related genes (DE-MiRGs) in individuals with UC were identified using the \"Limma\" R package. Unsupervised consensus clustering was utilized to determine the intrinsic subtypes of UC driven by DE-MiRGs. Weighted gene co-expression network analysis was employed to investigate module genes related to UC. Four machine learning algorithms were utilized for screening DE-MiRGs in UC and construct MiRGs diagnostic models. The models were developed utilizing the over-sampled training cohort, followed by validation in both the internal test cohort and the external validation cohort. Immune cell infiltration was assessed using the Xcell and CIBERSORT algorithms, while potential biological mechanisms were explored through GSVA and GSEA algorithms. Hub genes were selected using the PPI network.
UNASSIGNED: The study identified 108 DE-MiRGs in the colonic mucosa of patients with UC compared to healthy controls, showing significant enrichment in pathways associated with mitochondrial metabolism and inflammation. The MiRGs diagnostic models for UC were constructed based on 17 signature genes identified through various machine learning algorithms, demonstrated excellent predictive capabilities. Utilizing the identified DE-MiRGs from the normalized compendium, 941 patients with UC were stratified into three subtypes characterized by distinct cellular and molecular profiles. Specifically, the metabolic subtype demonstrated enrichment in epithelial cells, the immune-inflamed subtype displayed high enrichment in antigen-presenting cells and pathways related to pro-inflammatory activation, and the transitional subtype exhibited moderate activation across all signaling pathways. Importantly, the immune-inflamed subtype exhibited a stronger correlation with superior response to four biologics: infliximab, ustekinumab, vedolizumab, and golimumab compared to the metabolic subtype.
UNASSIGNED: This analysis unveils the interplay between mitochondrial dysfunction and the immune microenvironment in UC, thereby offering novel perspectives on the potential pathogenesis of UC and precision treatment of UC patients, and identifying new therapeutic targets.
摘要：
■越来越多的证据表明线粒体功能障碍加剧了肠屏障功能障碍和炎症。尽管对线粒体功能障碍和溃疡性结肠炎（UC）的了解越来越多，UC线粒体功能障碍的机制仍有待充分探索。
■我们整合了来自全球12个多中心队列的1137个UC结肠粘膜样本，以创建标准化的纲要。使用“Limma”R包鉴定了UC个体中差异表达的线粒体相关基因（DE-MiRG）。利用无监督共识聚类来确定由DE-MiRG驱动的UC的内在亚型。采用加权基因共表达网络分析研究与UC相关的模块基因。利用四种机器学习算法在UC中筛选DE-MiRG并构建MiRG诊断模型。这些模型是利用过采样的训练队列开发的，然后在内部测试队列和外部验证队列中进行验证。使用Xcell和CIBERSORT算法评估免疫细胞浸润，同时通过GSVA和GSEA算法探索了潜在的生物学机制。使用PPI网络选择Hub基因。
■与健康对照相比，该研究确定了UC患者结肠粘膜中的108个DE-MiRGs，显示与线粒体代谢和炎症相关的通路显著富集。基于通过各种机器学习算法识别的17个特征基因，构建了UC的MiRGs诊断模型。展示了出色的预测能力。利用归一化汇编中确定的DE-MiRG，941例UC患者被分为三种亚型，其特征在于不同的细胞和分子谱。具体来说,代谢亚型在上皮细胞中表现出富集，免疫发炎的亚型在抗原呈递细胞和与促炎激活相关的途径中显示出高度富集，过渡亚型在所有信号通路中都表现出适度的激活。重要的是,免疫发炎的亚型表现出更强的相关性与四种生物制剂的优异反应：英夫利昔单抗，ustekinumab,维多珠单抗,和戈利木单抗与代谢亚型的比较。
■该分析揭示了UC中线粒体功能障碍与免疫微环境之间的相互作用，从而为UC的潜在发病机制和UC患者的精确治疗提供了新的观点，并确定新的治疗靶点。
■我们整合了来自全球12个多中心队列的1137个UC结肠粘膜样本，以创建标准化的纲要。使用“Limma”R包鉴定了UC个体中差异表达的线粒体相关基因（DE-MiRG）。利用无监督共识聚类来确定由DE-MiRG驱动的UC的内在亚型。采用加权基因共表达网络分析研究与UC相关的模块基因。利用四种机器学习算法在UC中筛选DE-MiRG并构建MiRG诊断模型。这些模型是利用过采样的训练队列开发的，然后在内部测试队列和外部验证队列中进行验证。使用Xcell和CIBERSORT算法评估免疫细胞浸润，同时通过GSVA和GSEA算法探索了潜在的生物学机制。使用PPI网络选择Hub基因。
■与健康对照相比，该研究确定了UC患者结肠粘膜中的108个DE-MiRGs，显示与线粒体代谢和炎症相关的通路显著富集。基于通过各种机器学习算法识别的17个特征基因，构建了UC的MiRGs诊断模型。展示了出色的预测能力。利用归一化汇编中确定的DE-MiRG，941例UC患者被分为三种亚型，其特征在于不同的细胞和分子谱。具体来说,代谢亚型在上皮细胞中表现出富集，免疫发炎的亚型在抗原呈递细胞和与促炎激活相关的途径中显示出高度富集，过渡亚型在所有信号通路中都表现出适度的激活。重要的是,免疫发炎的亚型表现出更强的相关性与四种生物制剂的优异反应：英夫利昔单抗，ustekinumab,维多珠单抗,和戈利木单抗与代谢亚型的比较。
■该分析揭示了UC中线粒体功能障碍与免疫微环境之间的相互作用，从而为UC的潜在发病机制和UC患者的精确治疗提供了新的观点，并确定新的治疗靶点。
